Driving Decision Strategy using Machine Learning Algorithms for Autonomous Vehicles

Autonomous vehicles are the core in the technology of automation and decision making. Indeed there are various parameters that need to address effectively for better results and least disaster. But the current self vehicles/ autonomous vehicles are in great juncture of capable understanding without any human interaction especially in the way of changing lanes various algorithms are in support of decision making. This paper suggests a Decision strategy for lane changing by applying some eminent algorithms like MLP, Random Forest and some genetic algorithms. Comparison of accuracy among these and suggesting a solution in form of Driving Decision Strategy based genetic algorithm is mentioned as the final outcome of the paper. Accuracy check is also made as in the results from which best option can be chosen accordingly with greater efficiency.